Vascular flow assessment

ABSTRACT

A method for vascular assessment is disclosed. The method comprises receiving a plurality of 2D angiographic images of a portion of a vasculature of a subject, and processing the images to produce a stenotic model over the vasculature, the stenotic model having measurements of the vasculature at one or more locations along vessels of the vasculature. The method further comprises obtaining a flow characteristic of the stenotic model, and calculating an index indicative of vascular function, based, at least in part, on the flow characteristic in the stenotic model.

FIELD AND BACKGROUND OF THE INVENTION

The present invention, in some embodiments thereof, relates to vascularflow assessment and, more particularly, but not exclusively, to modelingvascular flow and to assessing vascular flow.

Arterial stenosis is one of the most serious forms of arterial disease.In clinical practice, stenosis severity is estimated by using eithersimple geometrical parameter, such as determining the percent diameterof a stenosis, or by measuring hemodynamically based parameters, such asthe pressure-based myocardial Fractional Flow Reserve (FFR). FFR is aninvasive measurement of the functional significance of coronarystenoses. The FFR measurement technique involves insertion of a 0.014″guidewire equipped with a miniature pressure transducer located acrossthe arterial stenosis. It represents the ratio between the maximal bloodflow in the area of stenosis and the maximal blood flow in the sameterritory without stenosis. Earlier studies showed that FFR<0.75 is anaccurate predictor of ischemia and deferral of percutaneous coronaryintervention for lesions with FFR≧0.75 appeared to be safe.

An FFR cut-off value of 0.8 is typically used in clinical practice toguide revascularization, supported by long-term outcome data. Typically,an FFR value in a range of 0.75-0.8 is considered a ‘grey zone’ havinguncertain clinical significance.

Modeling vascular flow and to assessing vascular flow is described, forexample, in U.S. published patent application number 2012/0059246 ofTaylor, to a “Method And System For Patient-Specific Modeling Of BloodFlow”, which describes embodiments which include a system fordetermining cardiovascular information for a patient. The system mayinclude at least one computer system configured to receivepatient-specific data regarding a geometry of at least a portion of ananatomical structure of the patient. The portion of the anatomicalstructure may include at least a portion of the patient's aorta and atleast a portion of a plurality of coronary arteries emanating from theportion of the aorta. The at least one computer system may also beconfigured to create a three-dimensional model representing the portionof the anatomical structure based on the patient-specific data, create aphysics-based model relating to a blood flow characteristic within theportion of the anatomical structure, and determine a fractional flowreserve within the portion of the anatomical structure based on thethree-dimensional model and the physics-based model.

Additional Background Art Includes:

U.S. Published Patent Application No. 2012/053918 of Taylor;

U.S. Published Patent Application No. 2012/0072190 of Sharma et al;

U.S. Published Patent Application No. 2012/0053921 of Taylor;

U.S. Published Patent Application No. 2010/0220917 of Steinberg et al;

U.S. Published Patent Application No. 2010/0160764 of Steinberg et al;

U.S. Published Patent Application No. 2012/0072190 of Sharma et al;

U.S. Pat. No. 6,236,878 to Taylor et al;

U.S. Pat. No. 8,311,750 to Taylor;

an article titled: “Determination of fractional flow reserve (FFR) basedon scaling laws: a simulation study” by Jerry T. Wong and Sabee Molloi,published in Phys. Med. Biol. 53 (2008) 3995-4011;

an article titled: “A Scheme for Coherence-Enhancing Diffusion Filteringwith Optimized Rotation Invariance”, by Weickert, published in Journalof Visual

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a thesis in a book titled “Anisotropic Diffusion in Image Processing”,by J. Weickert, published by B. G. Teubner (Stuttgart) in 1998;

an article titled: “Multiscale vessel enhancement filtering”, by A. FFrangi, W. J. Niessen, K. L. Vincken, M. A. Viergever, published inMedical Image Computing and Computer-Assisted Intervention—MICCA '98;

an article titled: “Determination of fractional flow reserve (FFR) basedon scaling laws: a simulation study”, by Jerry T Wong and Sabee Molloi,published in Phys. Med. Biol. 53 (2008) 3995-4011;

an article titled: “Quantification of Fractional Flow Reserve UsingAngiographic Image Data”, by S. Molloi, J. T. Wong, D. A. Chalyan, andH. Le, published in O. Dössel and W. C. Schlegel (Eds.): WC 2009, IFMBEProceedings 25/II, pp. 901-904, 2009;

an article titled: “Quantification of fractional flow reserve based onangiographic image data”, by Jerry T. Wong, Huy Le, William M. Suh,David A. Chalyan, Toufan Mehraien, Morton J. Kern, Ghassan S. Kassab,and Sabee Molloi, published in Int J Cardiovasc Imaging (2012) 28:13-22;

an article titled: “An angiographic technique for coronary fractionalflow reserve measurement: in vivo validation”, by Shigeho Takarada,Zhang Zhang and Sabee Molloi, published online on 31 Aug. 2012 in Int JCardiovasc Imaging;

an article titled: “A new algorithm for deriving pulsatile blood flowwaveforms tested using stimulated dynamic angiographic data”, by A. M.Seifalian, D. J. Hawkes, A. C. Colchester, and K. E. Hobbs, published inNeuroradiology, vol. 31, no. 3, pp. 263269, 1989;

an article titled: “Validation of a quantitative radiographic techniqueto estimate pulsatile blood flow waveforms using digital subtractionangiographic data”, by A. M. Seifalian, D. J. Hawkes, C. R. Hardingham,A. C. Colchester, and J. F. Reidy, published in J. Biomed. Eng., vol.13, no., 3 pp. 225233, May 1991;

an article titled: “Validation of volume blood flow measurements usingthree dimensional distance-concentration functions derived from digitalX-ray angiograms”, by D. J. Hawkes, A. M. Seifalian, A. C. Colchester,N. Iqbal, C. R. Hardingham, C. F. Bladin, and K. E. Hobbs, published inInvest. Radiol, vol. 29, no. 4, pp. 434442, April 1994;

an article titled: “Blood flow measurements using 3Ddistance-concentration functions derived from digital X-ray angiograms”,by A. M. Seifalian, D. J. Hawkes, C. Bladin, A. C. F. Colchester, and K.E. F. Hobbs, published in Cardiovascular Imaging, J. H. C. Reiber and E.E. van der Wall, Eds. Norwell, MA, The Netherlands: Kluwer Academic,1996, pp. 425-442;

an article titled: “Determination of instantaneous and average bloodflow rates from digital angiograms of vessel phantoms usingdistance-density curves”, by K. R. Hoffmann, K. Doi, and L. E. Fencil,published in Invest. Radiol, vol. 26, no. 3, pp. 207212, March 1991;

an article titled: “Comparison of methods for instantaneous angiographicblood flow measurement”, by S. D. Shpilfoygel, R. Jahan, R. A. Close, G.R. Duckwiler, and D. J. Valentino, published in Med. Phys., vol. 26, no.6, pp. 862871, June 1999;

an article titled: “Quantitative angiographic blood flow measurementusing pulsed intra-arterial injection”, by D. W. Holdsworth, M.Drangova, and A. Fenster, published in Med. Phys., vol. 26, no. 10, pp.21682175, October 1999;

an article titled: “Dedicated bifurcation analysis: basic principles”,by Joan C. Tuinenburg, Gerhard Koning, Andrei Rares, Johannes P.Janssen, Alexandra J. Lansky, Johan H. C. Reiber, published in Int JCardiovasc Imaging (2011) 27:167174;

an article titled: “Quantitative Coronary Angiography in theInterventional Cardiology”, by Salvatore Davide Tomasello, Luca Costanzoand Alfredo Ruggero Galassi, published in Advances in the Diagnosis ofCoronary Atherosclerosis;

an article titled: “New approaches for the assessment of vessel sizes inquantitative (cardio-)vascular X-ray analysis”, by Johannes P. Janssen,Andrei Rares, Joan C. Tuinenburg, Gerhard Koning, Alexandra J. Lansky,Johan H. C. Reiber, published in Int J Cardiovasc Imaging (2010)26:259271;

an article titled: “Coronary obstructions, morphology and physiologicsignificance Quantitative Coronary Arteriography” by Kirkeeide R L. ed.Reiber J H C and Serruys P W, published by The Netherlands: Kluwer,1991, pp 229-44;

an article titled: “Coronary x-ray angiographic reconstruction and imageorientation”, by Kevin Sprague, Maria Drangova, Glen Lehmann, PiotrSlomka, David Levin, Benjamin Chow and Robert deKemp, published in MedPhys, 2006 March; 33(3):707-18;

an article titled: “A New Method of Three-dimensional Coronary ArteryReconstruction From X-Ray Angiography: Validation Against a VirtualPhantom and

Multislice Computed Tomography”, by Adamantios Andriotis, Ali Zifan,Manolis Gavaises, Panos Liatsis, Ioannis Pantos, Andreas Theodorakakos,Efstathios P. Efstathopoulos, and Demosthenes Katritsis, published inCatheter Cardiovasc Interv, 2008, January 1; 71(1):28-43;

an article titled: “Noninvasive Measurement of Coronary Artery BloodFlow Using Combined Two-Dimensional and Doppler Echocardiography”, byKenji Fusejima, MD, published in JACC Vol. 10, No. 5, November 1987:1024-31;

an article titled: “New Noninvasive Method for Coronary Flow ReserveAssessment: Contrast-Enhanced Transthoracic Second Harmonic EchoDoppler”, by Carlo Caiati, Cristiana Montaldo, Norma Zedda, AlessandroBina and Sabino Iliceto, published in Circulation, by the American HeartAssociation, 1999; 99:771-778;

an article titled: “Validation of noninvasive assessment of coronaryflow velocity reserve in the right coronary artery—A comparison oftransthoracic echocardiographic results with intracoronary Doppler flowwire measurements”, by Harald Lethena, Hans P Triesa, Stefan Kersting aand Heinz Lambertza, published in European Heart Journal (2003) 24,1567-1575;

an article titled: “Coronary flow: a new asset for the echo lab?” byPaolo Vocia, Francesco Pizzutoa and Francesco Romeob, published inEuropean Heart Journal (2004) 25, 1867-1879;

a review paper titled: “Non-invasive assessment of coronary flow andcoronary flow reserve by transthoracic Doppler echocardiography: a magictool for the real world”, by Patrick Meimoun and Christophe Tribouilloy,published in European Journal of Echocardiography (2008) 9, 449-457; and

an article titled: “Detection, location, and severity assessment of leftanterior descending coronary artery stenoses by means ofcontrast-enhanced transthoracic harmonic echo Doppler”, by Carlo Caiati,Norma Zedda, Mauro Cadeddu, Lijun Chen, Cristiana Montaldo, SabinoIliceto, Mario Erminio Lepera and Stefano Favale, published in EuropeanHeart Journal (2009) 30, 1797-1806.

The disclosures of all references mentioned above and throughout thepresent specification, as well as the disclosures of all referencesmentioned in those references, are hereby incorporated herein byreference.

SUMMARY OF THE INVENTION

In some embodiments of the invention, one or more models of a patient'svascular system are produced.

In some embodiments, a first model is produced from actual datacollected from images of the patient's vascular system. Optionally, theactual data includes a portion of the vascular system which includes atleast one blood vessel with stenosis. In these embodiments, the firstmodel describes a portion of the vasculature system which includes atleast one blood vessel with stenosis. This model is interchangeablyreferred to as a stenotic model. Optionally, the actual data includes aportion of the vascular system which includes at least one blood vesselwith stenosis and a crown. In these embodiments the stenotic model alsoincludes information pertaining to the shape and/or volume of the crown,and information pertaining to blood flow and/or resistance to blood flowin the crown.

In some embodiments the first model is used for calculating an indexindicative of vascular function. Preferably, the index is alsoindicative of potential effect of revascularization. For example, theindex can be calculated based on a volume of a crown in the model and ona contribution of a stenosed vessel to the resistance to blood flow inthe crown.

In some embodiments of the present invention a second model is producedfrom the actual data, changed so that one or more stenoses present inthe patient's vascular system are modeled as if they had beenrevascularized.

In some embodiments the first model and the second model are compared,and the index indicative of the potential effect of revascularization isproduced, based on comparing physical characteristics in the first modeland in the second model.

In some embodiments the index is a Fractional Flow Reserve (FFR), asknown in the art.

In some embodiments the index is some other measure which potentiallycorrelates to efficacy of performing revascularization of one or morevessels, optionally at locations of stenosis.

According to an aspect of some embodiments of the present inventionthere is provided a method for vascular assessment. The methodcomprises, receiving a plurality of 2D angiographic images of a portionof a vasculature of a subject; and using a computer for processing theimages and producing, within less than 60 minutes, a first vessel treeover a portion of the vasculature.

According to some embodiments of the invention the vasculature hastherein at least a catheter other than an angiographic catheter, andwherein the images are processed and the tree is produced while thecatheter is in the vasculature.

According to some embodiments of the invention the method comprisesusing the vascular model for calculating an index indicative of vascularfunction.

According to some embodiments of the invention the index is indicativeof the need for revascularization.

According to some embodiments of the invention the calculation is withinless than 60 minutes.

According to an aspect of some embodiments of the present inventionthere is provided a method of analyzing angiographic images. The methodcomprises: receiving a plurality of 2D angiographic images of a portionvasculature of a subject; and using a computer for processing the imagesto produce a tree model of the vasculature.

According to an aspect of some embodiments of the present inventionthere is provided a method of treating a vasculature. The methodcomprises: capturing a plurality of 2D angiographic images of a vascularsystem of a subject being immobilized on a treatment surface; and, whilethe subject remains immobilized: processing the images and producing avessel tree over the vascular system; identifying a constricted bloodvessel in the tree; and inflating a stent at a site of the vasculaturecorresponding to the constricted blood vessel in the tree.

According to some embodiments of the invention the plurality of 2Dangiographic images comprise at least three 2D angiographic images,wherein the tree model is a 3D tree model.

According to some embodiments of the invention the method comprisesidentifying in the first vessel tree a stenosed vessel and a crown ofthe stenosed vessel, and calculating a resistance to fluid flow in thecrown; wherein the index is calculated based on a volume of the crown,and on a contribution of the stenosed vessel to the resistance to fluidflow.

According to some embodiments of the invention the vessel tree comprisesdata pertaining to location, orientation and diameter of vessels at aplurality of points within the portion of the vasculature.

According to some embodiments of the invention the method comprisesprocessing the images to produce a second three-dimensional vessel treeover the vasculature, the second vessel tree corresponding to the firstvessel tree in which a stenotic vessel is replaced with an inflatedvessel; wherein the calculation of the index is based on the first treeand the second tree.

According to some embodiments of the invention the method comprisesprocessing the images to produce a second three-dimensional vessel treeover the vasculature, the second vessel tree corresponding to a portionof the vascular system which does not include a stenosis and which isgeometrically similar to the first vessel tree; wherein the calculationof the index is based on the first tree and the second tree.

According to some embodiments of the invention the method comprisesobtaining a Fractional Flow Ratio (FFR) based on the index.

According to some embodiments of the invention the method comprisesdetermining, based on the index, a ratio between maximal blood flow inan area of a stenosis and a maximal blood flow in a same area withoutstenosis.

According to some embodiments of the invention the method comprisesminimally invasively treating a stenosed vessel.

According to some embodiments of the invention the treatment is executedless than one hour from the calculation of the index.

According to some embodiments of the invention the method comprisesstoring the tree in a computer readable medium.

According to some embodiments of the invention the method comprisestransmitting the tree to a remote computer.

According to some embodiments of the invention the invention the methodcomprises capturing the 2D angiographic images.

According to some embodiments of the invention the capturing theplurality of 2D angiographic images is effected by a plurality ofimaging devices to capture the plurality of 2D angiographic images.

According to some embodiments of the invention the capturing theplurality of 2D angiographic images comprises synchronizing theplurality of imaging devices to capture the plurality of imagessubstantially at a same phase during a heart beat cycle.

According to some embodiments of the invention the synchronizing isaccording to the subject's ECG signal.

According to some embodiments of the invention the method comprises:detecting corresponding image features in each of N angiographic images,where N is an integer greater than 1; calculating image correctionparameters based on the corresponding image features; and based on thecorrection parameters, registering N−1 angiographic images togeometrically correspond to an angiographic image other than the N−1angiographic images.

According to some embodiments of the invention the method comprisesdefining a surface corresponding to a shape of the heart of the subject,and using the surface as a constraint for the detection of thecorresponding image features.

According to some embodiments of the invention the method comprisescompensating for breath and patient movement.

According to an aspect of some embodiments of the present inventionthere is provided a computer software product. The computer softwareproduct comprises a computer-readable medium in which programinstructions are stored, which instructions, when read by a computer,cause the computer to receive a plurality of 2D angiographic images of asubject's vascular system and execute the method as delineated above andoptionally as further detailed below.

According to an aspect of some embodiments of the present inventionthere is provided a system for vascular assessment. The systemcomprises: a plurality of imaging devices configured for capturing aplurality of 2D angiographic images of a vascular system of a subject;and a computer configured for receiving the plurality of 2D images andexecuting the method the method as delineated above and optionally asfurther detailed below.

According to an aspect of some embodiments of the present inventionthere is provided a system for vascular assessment comprising: acomputer functionally connected to a plurality of angiographic imagingdevices for capturing a plurality of 2D images of a portion ofvasculature of a subject, configured to: accept data from the pluralityof angiographic imaging devices; and process the images to produce atree model of the vasculature, wherein the tree model comprisesgeometric measurements of the vasculature at one or more locations alonga vessel of at least one branch of the vasculature.

According to some embodiments of the invention the system comprises asynchronization unit configured to provide the plurality of angiographicimaging devices with a synchronization signal for synchronizing thecapturing of the plurality of 2D images of the vasculature.

According to some embodiments of the invention the computer isconfigured to accept a subject ECG signal, and to select, based on theECG signal, 2D images corresponding to substantially a same phase duringa heart beat cycle.

According to some embodiments of the invention the system comprises animage registration unit configured for: detecting corresponding imagefeatures in each of N angiographic images, where N is an integer greaterthan 1; calculating image correction parameters based on thecorresponding image features; and based on the correction parameters,registering N−1 angiographic images to geometrically correspond to anangiographic image other than the N−1 angiographic images.

According to some embodiments of the invention the computer isconfigured for defining a surface corresponding to a shape of the heartof the subject, and using the surface as a constraint for the detectionof the corresponding image features.

According to some embodiments of the invention the computer isconfigured for compensating for breath and patient movement.

According to some embodiments of the invention the compensatingcomprises iteratively repeating the detection of the corresponding imagefeatures each time for a different subset of angiographic images, andupdating the image correction parameters responsively to the repeateddetection of the corresponding image features.

According to some embodiments of the invention N is greater than 2.According to some embodiments of the invention N is greater than 3.

According to some embodiments of the invention the corresponding imagefeatures comprise at least one of a group consisting of an origin of thetree model, a location of minimal radius in a stenosed vessel, and abifurcation of a vessel.

According to some embodiments of the invention the tree model comprisesdata pertaining to location, orientation and diameter of vessels at aplurality of points within the portion of the vasculature.

According to some embodiments of the invention tree model comprisingmeasurements of the vasculature at one or more locations along at leastone branch of the vasculature

According to some embodiments of the invention the geometricmeasurements of the vasculature are at one or more locations along acenterline of at least one branch of the vasculature.

According to some embodiments of the invention the tree model comprisesdata pertaining to blood flow characteristics in at one or more of theplurality of points.

According to some embodiments of the invention the portion of thevasculature comprises the heart arteries.

According to an aspect of some embodiments of the present inventionthere is provided a method for vascular assessment comprising: receivinga plurality of 2D angiographic images of a portion of a vasculature of asubject, and processing the images to produce a stenotic model over thevasculature, the stenotic model having measurements of the vasculatureat one or more locations along vessels of the vasculature; obtaining aflow characteristic of the stenotic model; and calculating an indexindicative of vascular function, based, at least in part, on the flowcharacteristic in the stenotic model.

According to some embodiments of the invention the flow characteristicof the stenotic model comprises resistance to fluid flow.

According to some embodiments of the invention the invention the methodcomprises identifying in the first stenotic model a stenosed vessel anda crown of the stenosed vessel, and calculating the resistance to fluidflow in the crown; wherein the index is calculated based on a volume ofthe crown, and on a contribution of the stenosed vessel to theresistance to fluid flow.

According to some embodiments of the invention the flow characteristicof the stenotic model comprises fluid flow.

According to some embodiments of the invention the stenotic model is athree-dimensional vessel tree.

According to some embodiments of the invention the vessel tree comprisesdata pertaining to location, orientation and diameter of vessels at aplurality of points within the portion of the vasculature.

According to some embodiments of the invention the processing comprises:extending the stenotic model by one bifurcation; calculating a new flowcharacteristic in the extended stenotic model; updating the indexresponsively to the new flow characteristic and according to apredetermined criterion; and iteratively repeating the extending, thecalculating and the updating.

According to some embodiments of the invention the method comprisesprocessing the images to produce a second model over the vasculature,and obtaining a flow characteristic of the second model; wherein thecalculation of the index is based on the flow characteristic in thestenotic model and on the flow characteristic in the second model.

According to some embodiments of the invention the method the secondmodel is a normal model, comprising an inflated vessel replacing astenotic vessel in the stenotic model.

According to some embodiments of the invention the stenotic model is athree-dimensional vessel tree and the second model is a secondthree-dimensional vessel tree.

According to some embodiments of the invention each of the modelscorresponds to a portion of the vasculature which is between twoconsecutive bifurcations of the vasculature and which includes astenosis.

According to some embodiments of the invention each of the modelscorresponds to a portion of the vasculature which includes a bifurcationof the vasculature.

According to some embodiments of the invention each of the modelscorresponds to a portion of the vasculature which includes a stenosisand which extends at least one bifurcation of the vasculature beyond thestenosis.

According to some embodiments of the invention the each of the modelscorresponds to a portion of the vasculature which includes a stenosisand which extends at least three bifurcations of the vasculature beyondthe stenosis.

According to some embodiments of the invention the method wherein eachof the models corresponds to a portion of the vasculature which includesa stenosis and which extends distally as far as resolution of the imagesallows.

According to some embodiments of the invention the stenotic modelcorresponds to a portion of the vasculature which includes a stenosis,and the second model corresponds to a portion of the vasculature whichdoes not include a stenosis and which is geometrically similar to thestenotic model.

According to some embodiments of the invention the processing comprises:extending each of the models by one bifurcation; calculating a new flowcharacteristic in each extended model; updating the index responsivelyto the new flow characteristics and according to a predeterminedcriterion; and iteratively repeating the extending, the calculating andthe updating.

According to some embodiments of the invention the index is calculatedbased on a ratio of the flow characteristic in the stenotic model to theflow characteristic in the second model.

According to some embodiments of the invention the index is indicativeof the need for revascularization.

According to an aspect of some embodiments of the present inventionthere is provided a method for vascular assessment including producing astenotic model of a subject's vascular system, the stenotic modelincluding measurements of the subject's vascular system at one or morelocations along a vessel centerline of the subject's vascular system,obtaining a flow characteristic of the stenotic model, producing asecond model, of a similar extent of the subject's vascular system asthe stenotic model, obtaining the flow characteristic of the secondmodel, and calculating an index indicative of the need forrevascularization, based on the flow characteristic in the stenoticmodel and on the flow characteristic in the second model.

According to some embodiments of the invention, the second model is anormal model, including an inflated vessel replacing a stenotic vesselin the stenotic model.

According to some embodiments of the invention, the vascular systemincludes the subject's heart arteries.

According to some embodiments of the invention, the producing a stenoticmodel of a subject's vascular system includes using a plurality ofangiographic imaging devices for capturing a plurality of 2D images ofthe subject's vascular system, and producing the stenotic model based onthe plurality of 2D images.

According to some embodiments of the invention, the flow characteristicincludes fluid flow.

According to some embodiments of the invention, the obtaining the flowcharacteristic of the stenotic model includes measuring fluid flow inthe subject's vascular system at the one or more locations in the extentof the subject's vascular system included in the stenotic model, and theobtaining the flow characteristic of the second model includescalculating fluid flow in the subject's vascular system at the one ormore locations in the extent of the subject's vascular system includedin the second model, based, at least in part, on correcting the fluidflow of the stenotic model to account for an inflated vessel.

According to some embodiments of the invention, the flow characteristicincludes resistance to fluid flow.

According to some embodiments of the invention, the obtaining the flowcharacteristic of the stenotic model includes calculating a resistanceto flow based, at least in part, on the subject vascular system crosssectional area at the one or more locations in the extent of thesubject's vascular system included in the stenotic model, and obtainingthe flow characteristic of the second model includes calculating theresistance to flow based, at least in part, on the subject vascularsystem inflated cross sectional area at the one or more locations in theextent of the subject's vascular system included in the second model.

According to some embodiments of the invention, the extent of each oneof the stenotic model and the second model includes a segment of thevascular system, between two consecutive bifurcations of the vascularsystem, which includes a stenosis.

According to some embodiments of the invention, the extent of each oneof the stenotic model and the second model includes a segment of thevascular system which includes a bifurcation of the vascular system.

According to some embodiments of the invention, each one of the stenoticmodel and the second model include an extent of the vascular systemwhich includes a stenosis and extends at least one bifurcation of thevascular system beyond the stenosis.

According to some embodiments of the invention, each one of the stenoticmodel and the second model include an extent of the vascular systemwhich includes a stenosis and an inflated stenosis respectively andextends at least three bifurcations of the vascular system beyond thestenosis.

According to some embodiments of the invention, each one of the stenoticmodel and the second model include an extent of the vascular systemwhich includes a stenosis and extends distally as far as resolution ofan imaging modality allows.

According to some embodiments of the invention, each one of the stenoticmodel and the second model include an extent of the vascular systemwhich includes a stenosis and extends distally at least one bifurcationof the vascular system beyond the stenosis, and further includingstoring the flow characteristic of the stenotic model as a previous flowcharacteristic of the stenotic model and storing the flow characteristicof the second model as a previous flow characteristic of the secondmodel, extending the extent of the stenotic model and the second modelby one more bifurcation, calculating a new flow characteristic in thestenotic model and calculating a new flow characteristic in the secondmodel, deciding whether to calculate the index indicative of the needfor revascularization as follows: if the new flow characteristic of thestenotic model differs from the previous characteristic of the stenoticmodel by less than a first specific difference, and the new flowcharacteristic of the second model differs from the previouscharacteristic of the second model by less than a second specificdifference, then calculating the index indicative of the need forrevascularization, else repeating the storing, the extending, thecalculating, and the deciding.

According to some embodiments of the invention, the stenotic modelincludes an extent of the vascular system which includes a stenosis, thesecond model includes an extent of the vascular system which does notinclude a stenosis and which is geometrically similar to the firstmodel.

According to some embodiments of the invention, the index is calculatedas a ratio of the flow characteristic in the stenotic model to the flowcharacteristic in the second model.

According to some embodiments of the invention, the calculated index isused to determine a Fractional Flow Ratio (FFR).

According to some embodiments of the invention, the calculated index isused to determine a ratio between maximal blood flow in an area ofstenosis and a maximal blood flow in a same area without stenosis.

According to some embodiments of the invention, the producing a stenoticmodel, the obtaining a flow characteristic of the stenotic model, theproducing a second model, the obtaining the flow characteristic of thesecond model, and the calculating an index, are all performed during adiagnostic catheterization, before a catheter used for the diagnosticcatheterization is withdrawn from the subject's body.

According to an aspect of some embodiments of the present inventionthere is provided a method for vascular assessment including capturing aplurality of 2D angiographic images of a subject's vascular system,producing a tree model of the subject's vascular system, the tree modelincluding geometric measurements of the subject's vascular system at oneor more locations along a vessel centerline of at least one branch ofthe subject's vascular system, using at least some of the plurality ofcaptured 2D angiographic images, and producing a model of a flowcharacteristic of the first tree model.

According to some embodiments of the invention, the vascular systemincludes the subject's heart arteries.

According to some embodiments of the invention, the capturing aplurality of 2D angiographic images includes using a plurality ofimaging devices to capture the plurality of 2D angiographic images.

According to some embodiments of the invention, the capturing aplurality of 2D angiographic images includes synchronizing the pluralityof imaging devices to capture the plurality of images at a same moment.

According to some embodiments of the invention, the synchronizing usesthe subject's ECG signal.

According to some embodiments of the invention, the synchronizingincludes detecting corresponding image features in at least a first 2Dangiographic image and a second 2D angiographic image of the pluralityof 2D angiographic images, calculating image correction parameters basedon the corresponding image features, and registering at least the second2D angiographic image to geometrically correspond to the first 2Dangiographic image, wherein the corresponding image features include atleast one of a group consisting of an origin of the tree model, alocation of minimal radius in a stenosed vessel, and a bifurcation of avessel.

According to an aspect of some embodiments of the present inventionthere is provided a system for vascular assessment including a computerfunctionally connected to a plurality of angiographic imaging devicesfor capturing a plurality of 2D images of a patient's vascular system,configured to accept data from the plurality of angiographic imagingdevices, produce a tree model of the subject's vascular system, whereinthe tree model includes geometric measurements of the subject's vascularsystem at one or more locations along a vessel centerline of at leastone branch of the subject's vascular system, using at least some of theplurality of captured 2D images, and produce a model of flowcharacteristics of the tree model.

According to some embodiments of the invention, the vascular systemincludes the subject's heart arteries.

According to some embodiments of the invention, further including asynchronization unit configured to provide the plurality of angiographicimaging devices with a synchronization signal for synchronizing thecapturing of the plurality of 2D images of the subject's vascularsystem.

According to some embodiments of the invention, further including asynchronization unit configured to accept a subject ECG signal, and toselect 2D images from the data from the plurality of angiographicimaging devices at a same cardiac phase in the 2D images.

According to some embodiments of the invention, further including animage registration unit configured to detect corresponding imagefeatures in at least a first 2D image and a second 2D image from thedata from the plurality of angiographic imaging devices, to calculateimage correction parameters based on the corresponding image features,and to register at least the second 2D image to geometrically correspondto the first 2D image, wherein the corresponding image features includeat least one of a group consisting of an origin of the tree model, alocation of minimal radius in a stenosed vessel, and a bifurcation of avessel.

According to an aspect of some embodiments of the present inventionthere is provided a method for vascular assessment including producing astenotic model of a subject's vascular system, the stenotic modelincluding geometric measurements of the subject's vascular system at oneor more locations along a vessel centerline of the subject's vascularsystem, including an extent of the vascular system which includes astenosis and extends at least one bifurcation of the vascular systembeyond the stenosis, obtaining a flow characteristic of the stenoticmodel, producing a second model, of a similar extent of the subject'svascular system as the stenotic model, obtaining the flow characteristicof the second model, and calculating an index indicative of the need forrevascularization, based on the flow characteristic in the stenoticmodel and on the flow characteristic in the second model, and furtherincluding storing the flow characteristic of the stenotic model as aprevious flow characteristic of the stenotic model and storing the flowcharacteristic of the second model as a previous flow characteristic ofthe second model, extending the extent of the stenotic model and thesecond model by one more bifurcation, calculating a new flowcharacteristic in the stenotic model and calculating a new flowcharacteristic in the second model, deciding whether to calculate theindex indicative of the need for revascularization as follows: if thenew flow characteristic of the stenotic model differs from the previouscharacteristic of the stenotic model by less than a first specificdifference, and the new flow characteristic of the second model differsfrom the previous characteristic of the second model by less than asecond specific difference, then calculating the index indicative of theneed for revascularization, else repeating the storing, the extending,the calculating, and the deciding.

Unless otherwise defined, all technical and/or scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of embodiments of the invention, exemplarymethods and/or materials are described below. In case of conflict, thepatent specification, including definitions, will control. In addition,the materials, methods, and examples are illustrative only and are notintended to be necessarily limiting.

Implementation of the method and/or system of embodiments of theinvention can involve performing or completing selected tasks manually,automatically, or a combination thereof. Moreover, according to actualinstrumentation and equipment of embodiments of the method and/or systemof the invention, several selected tasks could be implemented byhardware, by software or by firmware or by a combination thereof usingan operating system.

For example, hardware for performing selected tasks according toembodiments of the invention could be implemented as a chip or acircuit. As software, selected tasks according to embodiments of theinvention could be implemented as a plurality of software instructionsbeing executed by a computer using any suitable operating system. In anexemplary embodiment of the invention, one or more tasks according toexemplary embodiments of method and/or system as described herein areperformed by a data processor, such as a computing platform forexecuting a plurality of instructions. Optionally, the data processorincludes a volatile memory for storing instructions and/or data and/or anon-volatile storage, for example, a magnetic hard-disk and/or removablemedia, for storing instructions and/or data. Optionally, a networkconnection is provided as well. A display and/or a user input devicesuch as a keyboard or mouse are optionally provided as well.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments of the invention are herein described, by way ofexample only, with reference to the accompanying drawings and images.With specific reference now to the drawings and images in detail, it isstressed that the particulars shown are by way of example and forpurposes of illustrative discussion of embodiments of the invention. Inthis regard, the description taken with the drawings makes apparent tothose skilled in the art how embodiments of the invention may bepracticed.

In the drawings:

FIG. 1 depicts an original image and a Frangi-filter processed image,processed according to an example embodiment of the invention;

FIG. 2 depicts a light-colored center line overlaid on top of theoriginal image of FIG. 1, according to an example embodiment of theinvention;

FIG. 3A is an image of a coronary vessel tree model, produced accordingto an example embodiment of the invention;

FIG. 3B is an image of a coronary vessel tree model of FIG. 3A, withtree branch tags added according to an example embodiment of theinvention;

FIG. 3C is a simplified illustration of a tree model of a coronaryvessel tree, produced according to an example embodiment of theinvention;

FIG. 4 is a set of nine graphical illustrations of vessel segment radiiproduced according to an example embodiment of the invention, along thebranches of the coronary vessel tree model depicted in FIG. 3C, as afunction of distance along each branch;

FIG. 5 depicts a coronary tree model, a combination matrix depictingtree branch tags, and a combination matrix depicting tree branchresistances, all produced according to an example embodiment of theinvention;

FIG. 6 depicts a tree model of a vascular system, with tags numberingoutlets of the tree model, produced according to an example embodimentof the invention, the tags corresponding to stream lines;

FIG. 7 is a simplified illustration of a vascular tree model producedaccording to an example embodiment of the invention, including branchresistances Ri at each branch and a calculated flow Qi at each streamline outlet;

FIG. 8 is a simplified flow chart illustration of an example embodimentof the invention;

FIG. 9 is a simplified flow chart illustration of another exampleembodiment of the invention;

FIG. 10 is a simplified flow chart illustration of yet another exampleembodiment of the invention;

FIG. 11 is a simplified drawing of vasculature which includes a stenosedvessel and a non-stenosed vessel;

FIG. 12A is a simplified illustration of a hardware implementation of asystem for vascular assessment constructed according to an exampleembodiment of the invention; and

FIG. 12B is a simplified illustration of another hardware implementationof a system for vascular assessment constructed according to an exampleembodiment of the invention.

DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

The present invention, in some embodiments thereof, relates to vascularflow assessment and, more particularly, but not exclusively, to modelingvascular flow and to assessing vascular flow.

Before explaining at least one embodiment of the invention in detail, itis to be understood that the invention is not necessarily limited in itsapplication to the details of construction and the arrangement of thecomponents and/or methods set forth in the following description and/orillustrated in the drawings. The invention is capable of otherembodiments or of being practiced or carried out in various ways.

It is noted that in example embodiments described below, the coronaryvessel system, and more specifically the coronary artery system, isused. The example is not meant to limit embodiments of the invention tothe coronary arteries, as embodiments of the invention potentially applyto other vessel systems, such as, for example, the vein system and thelymph system.

In some embodiments, a first model of vascular flow in a subject, basedon imaging the subject's vascular system, is constructed. Typically, thefirst model is constructed of a vascular system which includes a problemsection of the vascular system, such as a stenosis in at least part of avessel. In some embodiments of the present invention the first modelcorresponds to a portion the vascular system which includes at least oneblood vessel with stenosis. In these embodiments, the first modeldescribes a portion of the vasculature system which includes at leastone blood vessel with stenosis and a crown. In these embodiments thefirst model optionally and preferably includes information pertaining tothe shape and/or volume of the crown, and information pertaining toblood flow and/or resistance to blood flow in the stenosed blood vesseland/or the crown.

Typically, but not necessarily, a second model is constructed. Thesecond model optionally and preferably describes a healthy vascularsystem corresponding to the first model. In some embodiments the secondmodel is constructed by changing a stenosis in the first model to bemore open, as it would be if a stent were to open the stenosis; and insome embodiments the second model is constructed by choosing a sectionof the subject's vascular system which includes a healthy vessel similarto the problem vessel of the first model.

Various ways of constructing the models are described below in moredetail.

In some embodiments, an index indicative of the need forrevascularization is calculated. This can be done based on the firstmodel or based on a comparison between the first and the second modelsof the vascular flow. The index is optionally used similarly to the FFRindex, to assess whether a stenosed vessel affects flow in the vascularsystem to such an extent that the prognosis for improvement in thesubject's condition following inflation of the stenosed vessel, ishigher than the likelihood for complications resulting from theinflation itself.

The terms “FFR” and “FFR index” in all their grammatical forms are usedthroughout the present specification and claims to stand for theabove-mentioned index, and not only for the FFR index mentioned in theBackground section as an invasive measurement involving insertion of aguidewire equipped with a miniature pressure transducer across thestenosis.

Acquiring Data for Constructing a Vascular Model

Data for modeling a vascular system may be collected from varioussources.

In some embodiments, the data is from minimally invasive angiographicimages. In some embodiments, the angiographic images aretwo-dimensional, and data from more than one angiographic image, takenfrom different viewing angles, is optionally used to produce a modelwhich includes three-dimensional data inferred from the two-dimensionalangiographic images taken from the different viewing angles.

In some embodiments, the data is from computerized tomography (CT)scans.

It is noted that under present day technology, angiographic imagesprovide a finer resolution than CT scans. Models of the vascular systemconstructed based on angiographic images, whether 1D tree models or full3D models, are potentially more accurate than models based on CT scans,and potentially provide a more accurate vascular assessment.

Constructing a Vascular Model

In some embodiments, the vascular system model is a tree model,optionally and preferably a three-dimensional tree model.

The tree model is a tree data structure having nodes linked bycurvilinear segments. The nodes are associated with vascular furcations(e.g., bifurcation or trifurcations or multi-furcations), and thecurvilinear segments are associated with vessel segments. A curvilinearsegment of the tree is referred to below as a branch, and the entiretree portion distal to a branch is referred as a crown.

Thus, tree model describes the vascular system by assigning nodes of thetree to vascular furcations and branches of the tree to vessel segmentsof the vascular system.

In some embodiments, the tree model may be represented by a series ofdisks or poker chips (e.g., circular or eliptical disks) that are linkedtogether to form a three-dimensional structure containing informationrelating to the local size, shape, branching, and other structuralfeatures at any point in the vascular tree.

In some embodiments, trifurcations and/or multi-furcations aremethodically converted to a combination of bifurcations. For example atrifurcation is optionally converted to two bifurcations. The term“bifurcation” in all its grammatical forms is used throughout thepresent specification and claims to mean bifurcation, trifurcation, ormulti-furcation.

In some embodiments the tree model includes data describing severalspecific points along each branch in the model. In some embodiments,data associated with branches of the tree includes geometricalproperties of the vessel at the branch, or at a specific point of thebranch. In some embodiments, the geometrical properties includelocation, orientation and diameter of vessels at a plurality of pointswithin a portion of the vasculature. The geometrical properties can alsoinclude a cross sectional area of the vessel at the specific point,and/or a radius of the vessel at the specific point. The tree model canalso comprise flow characteristics at one or more of the points.

In some embodiments the tree model is produced using geometric datameasured along vessel centerlines of a vascular system.

In some embodiments, the vascular system model is a three-dimensionalmodel, for example a three-dimensional model as may be obtained from aCT scan, and/or as may be constructed from a set of two-dimensionalangiographic images taken from different angles.

In some embodiments, the vascular system model is a one-dimensionalmodel, modeling segments of vessels as lines, which are one-dimensional,along center lines of a set of vessels of a vascular system.

In some embodiments, the one-dimensional model is a tree model of thevascular system, including data about segments which includes where asegment splits into two or more segments along a vessel.

In some embodiments the model includes a collection of data alongsegments of the vessels, including three dimensional data associatedwith a one-dimensional collection of points—for example, data about across sectional area at each point, and/or data about athree-dimensional direction of a segment, and/or data about an angle ofbifurcation, and so on.

In some embodiments, the model of the vascular system is used tocalculate a physical model of fluid flow, including physicalcharacteristics such as pressure and/or flow rate, and/or flowresistance, and/or shear stress, and/or flow velocity.

It is noted that performing calculations for a one-dimensionalcollection of points, such as calculations of resistance to fluid flow,is potentially much more efficient than performing such calculationsusing a full three-dimensional model which includes all voxels of avascular system.

A preferred procedure for producing a tree model is as follows.Corresponding image features are identified in each of a plurality ofangiographic images (e.g., in each captured image). An image feature canbe, for example, a furcation of a vessel, a location of minimal radiusin a stenosed vessel, and the like. In some embodiments of the presentinvention, a surface corresponding to a shape of the heart of thesubject is defined. This surface is optionally and preferably used as aconstraint for the detection of the corresponding image features. Such asurface can be defined using any technique known in the art, including,without limitation, polyhedra stitching.

Image correction parameters can then be calculated based on theidentified corresponding image features. The correction parameterstypically describe translation and/or rotation of the system ofcoordinates a particular image. Based on the calculated parameters, theangiographic images are registered to provide to provide mutualgeometrically correspondence thereamongst. Typically, several images areregistered relative to one of the images. For example, whencorresponding image features are identified in N images (e.g., N=2, 3, 4or more) one of the images can be selected as a reference, while theregistration is applied for the remaining N−1 angiographic images suchthat each of those remaining images geometrically corresponds to thesingle angiographic image that was selected as a reference. Otherregistration scenarios (e.g., pairwise registration) are not excludedfrom the scope of the present invention.

In various exemplary embodiments of the invention the procedurecompensates for breath and patient movement. This is optionally andpreferably done by iteratively repeating the detection of thecorresponding image features, each time for a different subset ofangiographic images, and updating the image correction parametersresponsively to the repeated detection. For example, in each iteration,a subset of the centerlines is analyzed to provide a three-dimensionalvolume occupied by the subset of centerlines. The skeleton of thisvolume can then be computed and project on one or more of the remaining2D images that were not included in the analysis. The image correctionparameters of these remaining images are then updated so as to reducethe offset between the projected line and the centerline in the 2Dimage. It was found by the present inventors that such an iterativeprocess significantly reduces the effects of breath, patient movements,and heart phase difference.

The computational procedure of the present embodiments is simpler thanconventional techniques which employ computational fluid dynamicssimulation and analysis. It is recognized that computational fluiddynamics require substantial computation power and/or time. For example,several days CPU times are required when fluid dynamics simulation isexecuted on a standard PC. While this time can be somewhat reduced usinga super-computer applying parallel processing, such a computationplatform is hardly available in medical facilities. The computationalprocedure of the present embodiments is not based on fluid dynamicsimulations and can therefore be implemented on a standard computingplatform, without the need for a super-computer.

The present inventors found that a tree model according to someembodiments of the present invention can be provided within less than 60minutes or less than 50 minutes or less than 40 minutes or less than 30minutes or less than 20 minutes from the time at which the 2D images arereceived by the computer. This allows the present embodiments toefficiently combine between the computation and treatment, wherein thetree model is optionally and preferably produced while the subject isimmobilized on a treatment surface (e.g., a bed) for the purpose ofcatheterization. In some embodiments of the present invention the treemodel is produced while the subject has a catheter in his or hervasculature. In some embodiments of the present invention thevasculature has at least one catheter other than an angiographiccatheter, (e.g., a cardiac catheter or an intracranial catheter),wherein the images are processed and the tree is produced while thecatheter is in the vasculature.

Vascular Assessment

In some embodiments of the present invention the stenotic model is usedfor calculating an index indicative of vascular function. The index canalso be indicative of the need for revascularization. A representativeexample of an index suitable for the present embodiments includes,without limitation, FFR.

In some embodiments, the index is calculated based on a volume of acrown in the stenotic model and on a contribution of a stenosed vesselto the resistance to blood flow in the crown. In some embodiments, theFFR index is calculated as a ratio of flow resistance of a stenosedvessel in a vascular model which includes the stenosed vessel to flowresistance of an inflated version of the same vessel in a similarvascular model where the stenosed vessel was mathematically inflated.

In some embodiments, the index is calculated as a ratio of flowresistance of a stenosed vessel in a vascular model to flow resistanceof a neighboring similar healthy vessel in the vascular model. The ratiomay be multiplied by a constant which accounts for different geometriesof the stenosed vessel and the neighboring vessel, as described below inthe section titled “Producing a model of physical characteristics of avascular system”.

In some embodiments, a first tree model of a vascular system isproduced, based on actual patient measurements, optionally containing astenosis in one or more locations of the patient's vessels, and a secondtree model of the patient's vascular system is produced, optionallychanged so that at least one of the stenosis locations is modeled asafter revascularization, and an index indicative of the need forrevascularization is produced, based on comparing physicalcharacteristics of the first model and the second model.

In some embodiments, actual pressure and/or flow measurements are usedto calculate the physical characteristics in the model(s) and/or theabove-mentioned index.

In some embodiments, no actual pressure and/or flow measurements areused to calculate the physical characteristics in the model(s) and/orthe above-mentioned index.

It is noted that resolution of angiographic images is typically higherthan resolution typically obtained by 3D techniques such a CT. A modelconstructed from the higher resolution angiographic images, according tosome embodiments, can be inherently higher resolution, and providegreater geometric accuracy, and/or use of geometric properties ofsmaller vessels than CT images, and/or calculations using branchingvessels distal to a stenosis for more generations, or bifurcations,downstream from the stenosis than CT images.

Producing a Geometric Model of a Vascular System

Some example embodiments of methods for producing a geometric model of avascular system are now described.

One example embodiment of a method for producing a geometric model of avascular system includes producing a 3D model representing a vascularsystem, such as, by way of a non-limiting example, a coronary tree ofthe vascular system, from a set of 2D angiography images.

Reference is now made to FIG. 1, which depicts an original image 110 anda Frangi-filter processed image 120, processed according to an exampleembodiment of the invention.

The original image 110 depicts a typical angiogram 2D image.

In some embodiments, the original image 110 is further processed toenhance and detect vessels in the original image 110. By way of anon-limiting example, the Frangi-filter processed image 120 depicts theoriginal image 110 after image enhancement using a Frangi filter. Insome embodiments, vessel center-lines are determined for the angiogramsand/or for the vessel-enhanced angiograms.

Reference is now made to FIG. 2, which depicts a light-colored centerline 120 overlaid on top of the original image 110 of FIG. 1, accordingto an example embodiment of the invention.

The example method for producing a geometric model of a vascular systemoptionally includes:

extracting vessel center-lines from at least two 2D projections;

identifying homologous vessels in the different projections; and

applying epipolar geometry methods to obtain a 3D model of the coronarytree.

In some embodiments, the three dimensional model is optionally thinnedto produce a coronary vessel tree, as will be further described belowwith reference to FIGS. 3A, 3B and 3C.

In some embodiments, the coronary vessel tree includes a set of points,each of which may be a bifurcation or multi-furcation point in a tree,or a point along a branch of the tree.

In some embodiments, the three dimensional model is optionally used toestimate a diameter of the vessels.

In some embodiments, diameters of the vessels are recorded correspondingto at least some of the various points in the set of points are includedin the coronary vessel tree.

Motion Compensation

It is noted that when using two or more 2D projections of a subject'svessels, for example heart vessels, it may be desirable that the two ormore 2D projections be taken at the same time, or at least at a samephase during a heart beat cycle, so that the 2D projections be of a samevessel shape.

Deviations between the 2D projections might arise from cardiac, and/orrespiratory and/or patient motions between the 2D projection frames.

In some embodiments, to minimize deviations that might arise from lackof cardiac phase synchronization, an ECG output is used to choose a samecardiac phase in the 2D projections frames. Optionally, an ECG output isrecorded with a time scale, and a corresponding time scale is used torecord when images of the vascular system are captured.

In some embodiments 2D projection frames are selected to be at an end ofthe diastole phase of the cardiac cycle.

In some embodiments the heart is imaged under influence of intravenousadenosine, may exaggerate a difference between normal and abnormalsegments.

In some embodiments, to compensate for respiratory and patient motions,features are identified in the 2D projections. The features optionallyinclude an origin of the coronary vessel tree, and/or points of minimalradius in sick vessels, and/or bifurcations. The features optionally actas anchors to correct the coronary vessel tree position in space.

In some embodiments, the features are optionally also used to alignimages taken from different directions, or even used only for alignmentof images taken from different directions.

In some embodiments, to perform the correction, epipolar geometry isused to compute shift and/or rotation and/or expansion parameters whichresult in a best fit between the anchors.

Construction of a Vessel Tree Model

After reconstruction of a vessel tree model, such as a coronary tree,from angiographic images, the tree model is optionally divided intobranches, where a branch is defined as a section of a vessel betweenbifurcations. The branches are numbered according to their generation inthe tree.

Reference is now made to FIG. 3A, which is an image 305 of a coronaryvessel tree model 310, produced according to an example embodiment ofthe invention.

Reference is now also made to FIG. 3B, which is an image of a coronaryvessel tree model 315 of FIG. 3A, with tree branch tags 320 addedaccording to an example embodiment of the invention.

It is noted that the tags 320 are simply one example method for keepingtrack of branches in a tree model.

Reference is now also made to FIG. 3C, which is a simplifiedillustration of a tree model 330 of a coronary vessel tree, producedaccording to an example embodiment of the invention.

In some embodiments, the tree model is represented by a one-dimensionalarray. For example, the 9-branch tree in FIG. 3C is represented by a9-element array: a=[0 1 1 2 2 3 3 4 4], which lists tree nodes in abreadth-first order.

In some embodiments, during a reconstruction process, spatial locationand radius of segments on each branch are sampled every small distance,for example every 1 mm, or every 0.1 mm to every 5 mm.

In some embodiments, tree branches, corresponding to vessel segmentsbetween modeled bifurcations, correspond to vessel segments of a lengthof 1 mm, 5 mm, 10 mm, 20 mm, 50 mm, and even longer.

In some embodiments, sampling every small distance increases theaccuracy of a geometric model of the vessels, thereby increasingaccuracy of flow characteristics calculated based on the geometricmeasurements.

In some embodiments, the tree model may be a minimal tree, limited to asingle segment of a vessel, between two consecutive bifurcations of thevascular system.

Measuring Flow from Time Intensity Curves in Angiographic Sequences

In some embodiments, a physical model of fluid flow in the coronaryvessel tree is calculated, including physical characteristics such aspressure and/or flow rate, and/or flow resistance, and/or shear stress,and/or flow velocity.

In an example embodiment, a techniques based on the analysis ofconcentration-distance-time curves is used. The techniques perform wellin conditions of pulsatile flow. An example concentration-distance-timecurve technique is the concentration-distance curve matching algorithm.

Using the above-mentioned technique, a concentration of contrastmaterial, such as iodine, present at a particular distance along avessel segment, is found by integrating pixel intensities inangiogram(s) across a vessel lumen perpendicular to the centerline. Anoptimal shift is found in a distance axis between consecutiveconcentration-distance curves. A blood flow velocity is then calculatedby dividing the shift by the time interval between the curves. Severalvariations of the above technique have been reported in the followingreferences, the contents of which are hereby incorporated herein byreference: The four above-mentioned articles by Seifalian et al; theabove-mentioned article titled: “Determination of instantaneous andaverage blood flow rates from digital angiograms of vessel phantomsusing distance-density curves”, by Hoffmann et al; the above-mentionedarticle titled: “Comparison of methods for instantaneous angiographicblood flow measurement”, by Shpilfoygel et al; and the article titled:“Quantitative angiographic blood flow measurement using pulsedintra-arterial injection”, by Holdsworth et al.

Measuring Flow Using Other Modalities

In some embodiments flow is calculated from ultrasound measurements.Several variations of the above mentioned ultrasound technique have beenreported in above-mentioned references, the contents of which are herebyincorporated herein by reference: the above-mentioned article titled:“Noninvasive Measurement of Coronary Artery Blood Flow Using CombinedTwo-Dimensional and Doppler Echocardiography”, by Kenji Fusejima; thearticle titled: “New Noninvasive Method for Coronary Flow ReserveAssessment: Contrast-Enhanced Transthoracic Second Harmonic EchoDoppler”, by Carlo Caiati et al; the article titled: “Validation ofnoninvasive assessment of coronary flow velocity reserve in the rightcoronary artery—A comparison of transthoracic echocardiographic resultswith intracoronary Doppler flow wire measurements”, by Harald Lethena etal; the article titled: “Coronary flow: a new asset for the echo lab?”by Paolo Vocia et al; the review paper titled: “Non-invasive assessmentof coronary flow and coronary flow reserve by transthoracic Dopplerechocardiography: a magic tool for the real world”, by Patrick Meimounet al; and the article titled: “Detection, location, and severityassessment of left anterior descending coronary artery stenoses by meansof contrast-enhanced transthoracic harmonic echo Doppler”, by CarloCaiati et al.

In some embodiments, other modalities of measuring flow in the coronaryvessel tree are used. Example modalities include MRI flow measurementand SPECT (Single-photon emission computed tomography), or gamma camera,flow measurement.

It is noted that in some embodiments a vascular flow model isconstructed without using flow measurements or pressure measurements,based on geometrical measurement taken from images of the vascularsystem.

It is noted that in some embodiments flow measurements are used toverify flow characteristics calculated based on a model constructedbased on the geometric measurements.

It is noted that in some embodiments pressure measurements are used toverify flow characteristics calculated based on a model constructedbased on the geometric measurements.

An Example Embodiment of Producing a Model in which Stenoses are Modeledas if they Had been Revascularized—Stenosis Inflation

In some embodiments an estimation is made of a structure of a sickvessel as if the vessel has been revascularized to a healthy structure.Such a structure is termed an inflated structure—as if a stenosed vesselhas been revascularized back to normal diameter.

In some embodiments a technique is used as described in the followingreferences, the contents of which are hereby incorporated herein byreference: the article titled “Dedicated bifurcation analysis: basicprinciples”, by Tuinenburg et al; the article titled “QuantitativeCoronary Angiography in the Interventional Cardiology”, by Tomasello etal; and the article titled “New approaches for the assessment of vesselsizes in quantitative (cardio-)vascular X-ray analysis”, by Janssen etal.

A stenosis inflation procedure is optionally implemented for each one ofthe 2D projections separately. In some cases a stenosis may occur in aregion nearby to a bifurcation and in some cases the stenosis may occuralong a vessel. The stenosis inflation procedure in the two cases is nowdescribed separately.

If the stenosis is not located at a bifurcation region, it is enough toassess flow in the sick vessel. Coronary vessel segments proximal anddistal to the stenosis are relatively free of disease and are referredto as reference segments. An algorithm optionally calculates a coronaryedge by interpolating the coronary vessel segments considered free fromillness located proximally and distally to the region of stenosis withthe edges of the region of the stenosis. The algorithm optionallyreconstructs a reference coronary segment that is as if free fromdisease.

In some embodiments the technique includes calculation of a mean valueof the diameters of a vessel lumen in the segment of reference locatedupstream and downstream to the lesion.

If the stenosis is located at a bifurcation region, two examplebifurcation models are defined: a T-shape bifurcation model and aY-shape bifurcation model.

The bifurcation model, T-shape or Y-shape, is optionally detected byanalyzing arterial contours of three vessel segments connected to thebifurcation. Calculation of a flow model for an inflated healthy vesseldiameter is based on calculating as if each of the three segmentsconnected to the bifurcation has a healthy diameter. Such a calculationensures that both a proximal and a distal main (interpolated) referencediameter are based on arterial diameters outside the bifurcation core.

A reference diameter function of a bifurcation core is optionally basedon a reconstruction of a smooth transition between the proximal and thedistal vessel diameters. As a result, the reference diameter of theentire main section can be displayed as one function, composed of threedifferent straight reference lines linked together.

An Example of Producing a Model of Physical Characteristics of aVascular System

Some example embodiments of methods for producing a model of physicalcharacteristics of a vascular system are now described.

An example vascular system which will be used in the rest of thedescription below is the coronary vascular system.

In some embodiments of the invention, in order to evaluate an FFR indexin a stenosed branch of a vessel tree, a one dimensional model of thevessel tree is used to estimate the flow in the stenosed branch beforeand optionally also after stent implantation.

In some embodiments of the invention, in order to evaluate an FFR indexin a stenosed branch of a vessel tree, a one dimensional model of thevessel tree is used to estimate the flow in the stenosed branch beforeand optionally also after stenosis inflation.

Based on maximal peak flow of 500 mL/min and artery diameter of 5 mm, amaximal Reynolds number of the flow is:

$\begin{matrix}{{Re}_{peak\_ Flow} = {\frac{4Q_{peak\_ flow}}{\pi \; d_{\max}v} = {\frac{4 \cdot 500_{{mL}\text{/}\min}}{\pi \cdot 5_{\min} \cdot 3.5_{cP}} \approx 600}}} & {{Equation}\mspace{14mu} 5.1}\end{matrix}$

The above calculation assumes laminar flow. In laminar flow it isassumed, for example, that blood is a Newtonian and homogenous fluid.Another assumption which is optionally made is that flow in vesselbranches is one-dimensional and fully developed across the cross sectionof the vessel.

Based on the assumptions, a pressure drop in each segment of a vesseltree is approximated according to Poiseuille formulation in straighttubes:

Δ   P i = 128   µL i π   d i 4  Q i = i  Q i Equation   5.2

Where

is a viscous resistance to flow of a segment of the vessel. Minorlosses, due to bifurcations, constrictions and curvatures of the vesselsare optionally added as additional resistances in series, according tothe Darcy-Weisbach formulation:

$\begin{matrix}{{\Delta \; p} = {{\frac{\rho \; V^{2}}{2} \cdot {\sum K_{i}}} = {\frac{8\; \rho \; Q^{2}}{\pi^{2}d^{4}} \cdot {\sum K_{i}}}}} & {{Equation}\mspace{14mu} 5.3} \\{{(Q)} = {\frac{\Delta \; p}{Q} = {\left( {\frac{8\; \rho}{\pi^{2}d^{4}} \cdot {\sum K_{i}}} \right)Q}}} & {{Equation}\mspace{14mu} 5.4}\end{matrix}$

where K, are corresponding loss coefficients.

Reference is now made to FIG. 4, which is a set of nine graphicalillustrations 901-909 of vessel segment radii produced according to anexample embodiment of the invention, along the branches of the coronaryvessel tree model 330 depicted in FIG. 3C, as a function of distancealong each branch.

The resistance of a branch to flow is calculated as the sum of theindividual resistances of segments along the branch:

branch = ∫ L  8   μ π   r 4    l = 8   μ π  ∫ L   l r  ( l) 4    or Equation   5.5 branch = 8 × 0.035 g / cm · s π  ∑  l ir i 4 Equation   5.6

A resistance array corresponding to the example depicted in FIG. 3C is:

Rs=[808 1923 1646 1569 53394 10543 55341 91454 58225], where theresistance to flow is in units of mmHg*s/mL.

The above resistance array is for a vessel with stenosis, as evidencedby a peak of 91454 [mmHg*s/mL] in the resistance array.

A resistance array for a tree model without stenosis is optionallycalculated, based on Quantitative Coronary Angiography (QCA) methods forremoving stenoses greater than 50% in area.

In some embodiments, a tree model without stenosis is optionallycalculated by replacing a stenosed vessel by an inflated vessel, thatis, geometric measurements of a stenosed vessel section are replaced bymeasurements appropriate for an inflated vessel.

In some embodiments geometric data (diameter and/or cross-sectionalarea) which is used for the inflated vessel is a maximum of thegeometric data of the unstenosed vessel at a location just proximal tothe stenosed location and at a location just distal to the stenosedlocation.

In some embodiments geometric data (diameter and/or cross-sectionalarea) which is used for the inflated vessel is a minimum of thegeometric data of the unstenosed vessel at a location just proximal tothe stenosed location and at a location just distal to the stenosedlocation.

In some embodiments geometric data (diameter and/or cross-sectionalarea) which is used for the inflated vessel is an average of thegeometric data of the unstenosed vessel at a location just proximal tothe stenosed location and at a location just distal to the stenosedlocation.

In some embodiments geometric data (diameter and/or cross-sectionalarea) which is used for the inflated vessel is calculated as a linearfunction of the geometric data of the unstenosed vessel between alocation proximal to the stenosed location and a location distal to thestenosed location, that is, the inflated value is calculated taking intoaccount distances of the stenosed location from the proximal locationand from the distal location.

A stented, also termed inflated, resistance array for the exampledepicted in FIG. 4 is:

Rn=[808 1923 1646 1569 53394 10543 55341 80454 51225].

The peak resistance, which was 91454 [mmHg*s/mL], is replaced in theinflated, or stented model, by 80454 [mmHg*s/mL].

Reference is now made to FIG. 5, which depicts a coronary tree model1010, a combination matrix 1020 depicting tree branch tags, and acombination matrix 1030 depicting tree branch resistances, all producedaccording to an example embodiment of the invention.

The tree model is an example tree model with nine branches, tagged withbranch numbers 0, 1a, 1b, 2a, 2b, 3a, 3b, 4a and 4b.

The combination matrix 1020 includes nine rows 1021-1029, which containdata about nine stream lines, that is, nine paths through which fluidcan flow through the tree model. Five of the rows 1025-1029 include datafor five full stream lines, in darker text, for five paths which go afull way to outlets of the tree model. Four of the rows 1021-1024include data for partial streamlines, in lighter text, for four pathswhich are not fully developed in the tree model, and do not go a fullway to outlets of the tree model.

The combination matrix 1030 depicts rows for the same tree model asdepicted in the combination matrix 1020, with branch resistances locatedin matrix cells corresponding to branch tags in the combination matrix1020.

After calculating a resistance of each branch, stream lines are definedfrom the tree origin, branch 0 to each outlet. To keep track of thestream lines, branches which constitute each stream line are listed in acombination matrix, as shown for example in FIG. 5.

In some embodiments, defined stream lines are also numbered, as shown inFIG. 6.

Reference is now made to FIG. 6, which depicts a tree model 1100 of avascular system, with tags 1101-1105 numbering outlets of the tree model1100, produced according to an example embodiment of the invention, thetags corresponding to stream lines.

A pressure drop along a stream line j is calculated as a sum of pressuredrops at each of its component branches (i), according to:

dp _(j)=Σ

_(i) Q _(i)  Equation 5.7

when each branch has a different flow Qi.

Based on a principle of mass conservation at each bifurcation, the flowrate in a mother branch is the sum of flow rates of daughter branches.For example:

Q _(1a) =Q _(2a) +Q _(2b) =Q _(4a) +Q _(4b) +Q _(2b)  Equation 5.8

Thus, for example, a pressure drop along a stream line which ends atbranch 4a is:

                                 Equation  5.9 dp 4  a =  0  Q 0 +1  a  Q 1  a + 2  a  Q 2  a + 4  a  Q 4  a =  0  ( Q 4  a +Q 4  b + Q 2   b + Q 3  a + Q 3  b ) +   1  a  ( Q 4  a + Q 4 b + Q 2  b ) +  2  a  ( Q 4  a + Q 4  b ) +  4  a  Q 4  a ==  Q 4  a (  0 +  1  a +  2  a +  4  a ) + Q 4  b (  0 +  1 a +  2  a ) +  Q 2  b (  0 +  1  a ) + Q 3  a   0 + Q 3  b  0 = =  Q 4  ER 4 , 4 + Q 3  ER 4 , 5 + Q 1  ER 4 , 1 + Q 2  ER4 , 2 + Q 3  ER 4 , 3

where Qj is a flow rate along stream line j, and ER_(4J) is a sum ofcommon resistances of stream line j and stream line 4. A globalexpression is optionally formulated for the pressure drop along streamline j:

dp _(j) =ΣQ _(j) ER _(ij)  Equation 5.10

For a tree with k outlet branches, that is, for k full stream lines, aset of k linear equations are optionally used:

$\begin{matrix}{{{\begin{bmatrix}{ER}_{11} & {ER}_{12} & \ldots & \ldots & {ER}_{1k} \\{ER}_{21} & {ER}_{22} & \ldots & \ldots & {ER}_{2k} \\\ldots & \; & \; & \; & \; \\{ER}_{k\; 1} & {ER}_{k\; 2} & \ldots & \ldots & {ER}_{kk}\end{bmatrix}\begin{bmatrix}Q_{1} \\Q_{2} \\\ldots \\\; \\Q_{k}\end{bmatrix}} = \begin{bmatrix}{dp}_{1} \\{dp}_{2} \\\ldots \\\; \\{dp}_{k}\end{bmatrix}}{{\overset{\_}{\overset{\_}{A}} \times \overset{\_}{Q}} = \overset{\_}{DP}}} & {{Equation}\mspace{14mu} 5.11}\end{matrix}$

where indices 1 . . . k represent stream lines in the tree, and Q1 . . .Qk represent flow rates at corresponding outlet branches. The kXk matrixA consists of elements ER and is calculated from the combination matrix.

For example, for the 5 stream lines tree shown in FIG. 6, the ER matrixis:

                                                                                Equation  5.12ER = [ ( 0 + 1  a + 2  b ) ( 0 ) ( 0 ) ( 0 + 1  a ) ( 0 + 1  a ) ( 0) ( 0 + 1  b + 3  a ) ( 0 + 1  b ) ( 0 ) ( 0 ) ( 0 ) ( 0 + 1  b ) (0 + 1  b + 3  b ) ( 0 ) ( 0 ) ( 0 + 1  a ) ( 0 ) ( 0 ) ( 0 + 1  a +2  a + 4  a ) ( 0 + 1  a + 2  a ) ( 0 + 1  a ) ( 0 ) ( 0 ) ( 0 + 2 a + 2  a ) ( 0 + 1  a + 2  a + 4  b ) ] ${ER} = {\begin{bmatrix}56125 & 808 & 808 & 2731 & 2731 \\808 & 12997 & 2454 & 808 & 808 \\808 & 2454 & 57795 & 808 & 808 \\2731 & 808 & 808 & 95754 & 4300 \\2731 & 808 & 808 & 4300 & 55525\end{bmatrix}\mspace{920mu} {Equation}\mspace{14mu} 5.13}$

In some embodiments, fluid pressure measurements are made, for exampleblood pressure measurements. Based on provided fluid pressure boundaryconditions

(Pin and Pout_i), a vector DP is defined, and Qi is calculated:

Q=A ⁻¹ ×DP  Equation 5.14

For example, for a constant pressure drop of 70 mmHg between the originand all the outlets, the following flow distribution between the outletsis calculated:

Q=[1.4356, 6.6946, 1.2754, 0.7999, 1.4282], where the units of flow aremL/s. The result is an output of the above method, and is depicted inFIG. 7.

Reference is now made to FIG. 7, which is a simplified illustration of avascular tree model 1210 produced according to an example embodiment ofthe invention, including branch resistances Ri 1220 [mmHg*s/mL] at eachbranch and a calculated flow Qi 1230 [mL/s] at each stream line outlet.

In some embodiments, two models of a tree are calculated—a first modelwith stenoses, optionally as measured for a specific patient, and asecond model without stenoses. FFR is calculated for each branch usingthe formula:

$\begin{matrix}{{FFR} = \frac{Q_{S}}{Q_{N}}} & {{Equation}\mspace{14mu} 5.15}\end{matrix}$

For example, for the tree described above, the FFR calculated for eachone of the 9 branches is:

FFR=[1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.8846 0.8874]

Some Example Implementation of Calculating an Index

In some embodiments of the invention image processing techniques andnumerical calculations are combined for determining a physiologicalindex equivalent to the Fractional Flow Reserve (FFR). The integrationof the above-mentioned techniques potentially enables providing aminimally invasive assessment of blood flow during a diagnosticcatheterization, and provides an appropriate estimation of thefunctional significance of coronary lesions.

In some embodiments of the invention, a novel physiological indexprovides a physiological index which potentially enables evaluating theneed for percutaneous coronary intervention, and supports makingreal-time diagnostic and interventional (treatment) decisions. Theminimal-invasive method potentially prevents unnecessary risk to apatient, and may reduce time and cost of angiography, hospitalizationand follow-up.

In some embodiments a scientific model, based on patients' data, isprovided, which identifies geometrical characteristics of the patient'svascular system, or even a single vessel, and relevant hemodynamicinformation, equivalent to the present day invasive FFR method.

In addition, the model potentially allows examining a combination of 3Dreconstruction of the vessel and a numerical flow analysis forfunctional significance of a coronary lesion.

Some embodiments of the present invention perform a one-dimensionalreconstruction of the coronary artery during coronary angiography and acomputational/numerical flow analysis in order to evaluate the arterialpressure and/or flow rate and/or flow resistance along the culpritsegment.

Some embodiments of the present invention perform a three-dimensionalreconstruction of the coronary artery during coronary angiography and acomputational/numerical flow analysis in order to evaluate the arterialpressure and/or flow rate and/or flow resistance along the culpritsegment.

In embodiments of the invention in which the vascular function index iscalculated based only of the stenotic model, the resistance R_(s)contributed by a stenosis to the total resistance of the lesion's crownis evaluated. The volume V_(crown) of the crown distal to the stenosisis also calculated. An FFR index can then be calculated as a functionwhich decreases with R_(s) and V_(crown). A representative example ofsuch a function includes, without limitation,

$\begin{matrix}{{FFR}\left( {1 + \frac{R_{s}K\; V_{crown}^{3/4}}{P_{a} - P_{0}}} \right)}^{- 1} & {{Equation}\mspace{14mu} 5.15a}\end{matrix}$

where P_(a) is the aortic pressure, P₀ is the pre-capillary pressure andk is a scaling law coefficient which can be adapted to the aorticpressure.

Reference is now made to FIG. 8, which is a simplified flow chartillustration of an example embodiment of the invention. This embodimentis particularly useful when a vessel function index, such as FFR iscalculated based on two models of the vasculature.

FIG. 8 illustrates some portions of a method according to the exampleembodiment. The method includes receiving at least two 2D angiographicimages of a portion of a coronary artery of a patient (1810) andreconstructing a three-dimensional tree model of a coronary arterysystem (1815), and if there is a lesion, including the lesion.

A flow analysis of blood flow and optionally arterial pressure along asegment of interest, based on the tree model and optionally on otheravailable hemodynamic measurements, such as aortic pressure and/oramount of injected contrast.

The example embodiment just described potentially provides aminimally-invasive physiological index indicative of functionalsignificance of coronary lesions.

The example method is optionally performed during a coronary angiographyprocedure, and calculations are optionally performed during the coronaryangiography procedure, such that the minimally-invasive physiologicalindex is provided in real-time.

Reference is now made to FIG. 9, which is a simplified flow chartillustration of another example embodiment of the invention.

FIG. 9 illustrates a method for vascular assessment which includes:

producing a stenotic model of a subject's vascular system, the stenoticmodel comprising geometric measurements of the subject's vascular systemat one or more locations along a vessel centerline of at least onebranch of the subject's vascular system (1910);

obtain a flow characteristic of the stenotic model (1915);

producing a second model of a similar extent of the patient's vascularsystem as the stenotic model (1920);

obtaining the flow characteristic of the normal model (1925); and

calculating an index indicative of the need for revascularization, basedon the flow characteristic in the stenotic model and on the flowcharacteristic in the normal model (1930).

Reference is now made to FIG. 10, which is a simplified flow chartillustration of yet another example embodiment of the invention.

FIG. 10 illustrates a method for vascular assessment which includes:

capturing a plurality of 2D images of the subject's vascular system(2010);

producing a tree model of the subject's vascular system, the tree modelcomprising geometric measurements of the subject's vascular system atone or more locations along a vessel centerline of at least one branchof the subject's vascular system, using at least some of the pluralityof captured 2D images (2015); and

producing a model of flow characteristics of the first tree model(2020).

Extents of the Coronary Tree Model

In some embodiments, the extent of a first, stenosed model is justenough to include a stenosis, a section of vessel proximal to thestenosis, and a section of vessel distal to the stenosis.

In such an embodiment the extent of the first model may be, in somecases a segment of a vessel between bifurcations, including a stenosisin the segment. In some cases, especially when a stenosis is at abifurcation, the extent may include the bifurcation, and sections ofvessels proximal and distal to the stenosed bifurcation.

In some embodiments, an extent by which the first model extends proximalto the stenosis may be as small as 1 or 2 millimeters, up to as much as20 to 50 millimeters.

In some embodiments, an extent by which the first model extends distalto the stenosis may be as small as 1 or 2 millimeters, up to as much as20 to 50 millimeters.

In some embodiments, an extent by which the first model extends distalto the stenosis is measured by bifurcations of the vessel. In someembodiments, the first model extends distal to the stenosis by as few as1 or 2 bifurcations, and in some embodiments by as much as 3, 4, 5, andeven more bifurcations. In some embodiments the first model extendsdistal to the stenosis as far as resolution of the imaging processallows discerning distal portions of the vascular system.

A second model, of the same extent as the first model, is optionallyproduced, with the stenosis inflated as if the stenosis had beenrevascularized back to normal diameter.

Producing a Model of Physical Characteristics of a Vascular System

In an example implementation, given a proximal arterial pressure, P_(a),[mmHg], flow rate through a segment of interest Q_(s), [mL/s] isoptionally derived from a concentration of iodine contrast material,based on an analysis of concentration-distance-time curves, and ageometric description of the segment of interest, including diameterd(l) [cm], and/or volume V(l) [ml] as a function of segment length.

In some embodiments, especially in case of large vessels such as theLeft Anterior Descending coronary artery (LAD), blood flow can bemeasured for obtaining a flow model using a transthoracic echo Doppler,or other modalities such as MRI or SPECT.

For a given segment, a total resistance of the segment (R_(t),[mmHg*s/mL]) is optionally calculated by: dividing arterial pressure byflow rate:

$\begin{matrix}{R_{t} = \frac{P_{a}}{Q_{s}}} & {{Equation}\mspace{14mu} 5.16}\end{matrix}$

where R_(t) corresponds to total resistance, P_(a) corresponds toarterial pressure, and Q_(s) corresponds to flow rate through the vesselsegment.

From geometric description of the segment, a local resistance of thestenosis in the segment R_(s), [mmHg*s/mL] is estimated. Estimation ofRs may be made by any one or more of the following methods: using anempirical lookup table; and/or using a function such as described in theabove mentioned Kirkeeide reference; and/or by a cumulative summation ofPoiseuille resistances:

$\begin{matrix}{R_{s} = {\frac{128\mspace{14mu} \mu}{\pi}{\int\frac{l}{d^{4}}}}} & {{Equation}\mspace{14mu} 5.17}\end{matrix}$

where integration is over samples of the segment (dl), d is optionallyand arterial diameter of each sample, and μ is 0.035 g/cm·s isoptionally blood viscosity.

The segment's downstream resistance is calculated for the segment R_(n),[mmHg*s/mL] as follows:

R _(n) =R _(t) =R _(s)  Equation 5.18

A normal flow through the segment without stenosis Q_(n), [mL/s], iscalculated for example as follows:

$\begin{matrix}{Q_{n} = \frac{P_{a}}{R_{n}}} & {{Equation}\mspace{14mu} 5.19}\end{matrix}$

where Q_(a) is an input flow to the segment, P_(a) is pressure proximalto the segment, and R_(n) is resistance to flow by vessels distal to thesegment.

A Fractional Flow Reserve (FFR) is optionally derived as a ratio betweenmeasured flow rate through the stenosed segment and normal flow ratethrough the segment without stenosis:

$\begin{matrix}{{FFR} = \frac{Q_{s}}{Q_{n}}} & {{Equation}\mspace{14mu} 5.20}\end{matrix}$

In some embodiments, an index indicative of the potential effect ofrevascularization, such as an FFR index, is calculated using the datadescribed below:

proximal arterial pressure Pa, [mmHg] is measured;

a total inlet flow through a vessel origin, such as the coronary originQtotal, [mL/s], is derived from a concentration of contrast material(such as iodine), optionally based on the analysis ofconcentration-distance-time curves. In some embodiments, especially forlarge vessels such as the Left Anterior Descending (LAD) coronaryartery, flow is optionally recorded using a transthoracic echo Dopplerand/or other modalities such as MRI and SPECT;

a subject's specific anatomy, including one or more of the following:

-   -   a geometric description of arterial diameters along vessel tree        segments, for example up to 3-4 generations as a function of        segment length d(1) [cm];    -   a geometric description of arterial lengths along the vessel        tree segments (Li [cm]), for example up to 1-2 generations        downstream of the segment of interest, and an accumulative crown        length (L_(crown) [cm]) downstream to the segment of interest:        L_(crown)=ΣL_(i);    -   a geometric description of arterial volumes along the vessel        tree segments Vi [ml], for example up to 1-2 generations        downstream of the segment of interest, and the accumulative        crown volume (V_(crown) [ml]) downstream to the segment of        interest: V_(crown)=ΣV_(i);    -   a myocardial mass (LV mass) distribution for the arterial        segment of interest M [ml]. in some embodiments LV mass is        optionally calculated using, for example, a transthoracic echo        Doppler;    -   and

a reference parameter K or function F which correlates anatomicparameters such as described above with normal flow through the segment(without stenosis) Qn, [mL/s], for example:

Q _(n) =K*M or Q _(n) =F(M)  Equation 5.21

Using the above data, the index indicative of the potential effect ofrevascularization, such as the FFR index, is optionally calculated byperforming the following calculations for each vessel segment underconsideration:

from the geometric parameter of the tree, such as length, volume, massand/or diameter, a normal flow Qn in the segment is obtained;

from arterial pressure a resistance distal to the segment (Rn,[mmHg*s/mL]) is calculated, for example as follows:

${R_{n} = \frac{P_{a}}{Q_{n}}};$

from geometry a local resistance of the stenosis in the segment Rs,[mmHg*s/mL] is estimated, for example using one of the followingmethods:

-   -   a lookup table;    -   an empirical function such as described in the above mentioned        Kirkeeide reference; and/or    -   a cumulative summation of Poiseuille resistances

$R_{s} = {\frac{128\mspace{14mu} \mu}{\pi}{\int\frac{l}{d^{4}}}}$

where the integration is over samples of the segment (dl), d is anarterial diameter of each sample, and μ is 0.035 g/cm·s is optionallyblood viscosity;

the total resistance for the segment Rt [mmHg*s/mL] is optionallycalculated as: R_(t)=R_(n)+R_(s)

the flow through the stenosis segment Qs [mL/s] is optionally calculatedas:

${Q_{s} = \frac{P_{a}}{R_{t}}};$

and

the index, such as the fractional flow reserve (FFR), for the segment isoptionally calculated as:

${FFR} = {\frac{Q_{s}}{Q_{n}}.}$

It is noted that a sanity check for the above calculation can optionallybe made by checking if the accumulated flow in the tree agrees with themeasured total flow as follows: Q_(total)=ΣQ_(i).

In some embodiments, the extent of the first model is such that itincludes a stenosis, and extends distally as far as resolution of theimaging modality which produced the vessel model allows, and/or severalbifurcations, for example 3 or 4 bifurcations distally to the stenosis.

In an example implementation, a total inlet flow through a coronaryorigin is optionally derived from a concentration of contrast materialand optionally a subject's specific anatomy.

In some embodiments, data regarding the anatomy optionally includes ageometric description of arterial diameters along vessel segments up to3-4 bifurcations distally to a stenosis, a geometric description ofarterial lengths along vessel tree segments, a geometric description ofarterial volumes along the tree segments, and/or a myocardial mass (LVmass) distribution for the arterial segment of interest.

In some embodiments, data regarding the anatomy optionally includes ageometric description of arterial diameters along vessel segments as faras the imaging modality allows distally to a stenosis, a geometricdescription of arterial lengths along vessel tree segments, a geometricdescription of arterial volumes along the tree segments, and/or amyocardial mass (LV mass) distribution for the arterial segment ofinterest.

In some embodiments, LV mass is optionally calculated by using atransthoracic echo Doppler.

In some embodiments, a reference scaling parameter or function whichcorrelates anatomic parameters with normal flow through a segmentwithout stenosis is used.

In some embodiments, the extent of a first model includes a stenosedvessel, and a second model includes a similar extent of the vascularsystem, with a healthy vessel similar to the stenosed vessel.

An FFR index is optionally calculated from a ratio between the measuredflow rate in a stenosed vessel, and a flow rate in a neighboring healthyvessel. In some embodiments, the index is adjusted by a proportionbetween a total length of vessels in the crowns of the stenosed vesseland the healthy vessel. A crown of a vessel is hereby defined as asub-tree branching off the vessel. The total length of a crown isoptionally derived from a 3D reconstruction of the coronary tree.

Reference is now made to FIG. 11, which is a simplified drawing 2100 ofvasculature which includes a stenosed vessel 2105 and a non-stenosedvessel 2107.

FIG. 11 depicts two vessels which are candidates for basing a flowcharacteristic comparison of the stenosed vessel 2105 and thenon-stenosed vessel 2107. FIG. 11 also depicts the stenosed vessel crown2115 and the non-stenosed vessel crown 2117.

It is noted that the two vessels in FIG. 11 seem to be especially goodcandidates for the comparison, since both seem to have similardiameters, and both seem to have similar crowns.

According to scaling laws, a linear relationship exists between a normalflow rate Q in an artery, and a total length of vessels in its crown.This relationship holds for both the neighboring healthy vessel, and thestenosed vessel. For a healthy vessel:

Q _(N) ^(h) =k*L ^(h)  Equation 6.1

where Q_(N) ^(h) is a flow rate of a healthy vessel, k is a correctionfactor, and L^(h) is a total length of crown vasculature of the healthyvessel.

For a stenosed vessel, similarly:

Q _(N) ^(s) =k*L ^(s)  Equation 6.2

where Q_(N) ^(s) is a flow rate of a stenosed vessel, k is a correctionfactor, and L^(s) is a total length of crown vasculature of the stenosedvessel.

FFR is defined as a ratio between a flow rate in a stenosed arteryduring hyperemia, and the flow rate in the same artery in the absence ofthe stenosis (normal flow rate), as described by Equation 6.3 below. Theabove relationship yields a result for the FFR, calculated as a ratiobetween the measured flow rates in both vessels divided by the ratiobetween their respective total crown lengths.

It is noted that scaling laws also state the relationship between thenormal flow rate and the total crown volume. In some embodiments, theindex or FFR is optionally calculated from the above-mentioned ratiobetween the measured flow rates in the sick and healthy arteries,divided by a ratio between respective total crown volumes of a stenosedvessel and a normal vessel respectively, to the power of ¾.

$\begin{matrix}{{{FFR} \equiv \frac{Q_{S}^{s}}{Q_{N}^{s}}} = {\frac{Q_{S}^{s}}{k*L^{s}} = {\frac{Q_{S}^{s}}{\frac{Q_{N}^{h}}{L^{h}}*L^{s}} = {\left( \frac{Q_{S}^{s}}{Q_{N}^{h}} \right)*\frac{L^{h}}{L^{s}}}}}} & {{Equation}\mspace{14mu} 6.3}\end{matrix}$

Where Q_(N) ^(s) is an existing flow in a stenosed vessel, measured byany method described herein; Q_(N) ^(h) is an existing flow in a healthyvessel, measured by any method described herein; L^(s) is a total crownlength of the stenosed vessel; and L^(h) is a total crown length of thehealthy vessel.

The scaling laws also state a relationship between a normal flow rateand a total crown volume:

Q _(N) ^(h) =k _(v) *V _(h) ^(3/4)  Equation 6.4

where Q_(N) ^(h) is a flow rate of a healthy vessel, k_(v) is acorrection factor, and V_(h) is a total volume of crown vasculature ofthe healthy vessel.

For a stenosed vessel, similarly:

Q _(N) ^(s) =k _(v) *V _(s) ^(3/4)  Equation 6.5

where Q_(N) ^(s) is a flow rate of a stenosed vessel, k_(v) is acorrection factor, and V_(h) is a total volume of crown vasculature ofthe stenosed vessel.

An FFR is optionally calculated from the above-mentioned ratio betweenthe measured flow rates in the sick and healthy vessels, divided by theratio between the respective total crown volumes, raised to the power of¾:

$\begin{matrix}{{FFR} = {\left( \frac{Q_{S}^{s}}{Q_{N}^{h}} \right)*\left( \frac{V_{h}}{V_{s}} \right)^{3/4}}} & {{Equation}\mspace{14mu} 6.6}\end{matrix}$

where Vh and Vs are measured, by way of a non-limiting example, by usinga 3D model of the vasculature.

An Example Hardware Implementation

Reference is now made to FIG. 12A, which is a simplified illustration ofa hardware implementation of a system for vascular assessmentconstructed according to an example embodiment of the invention.

The Example System of FIG. 12A Includes:

Two or more imaging devices 2205 for capturing a plurality of 2D imagesof the patient's vascular system; a computer 2210 functionally connected2209 to the two or more imaging devices 2205.

The computer 2210 is optionally configured to: accept data from theplurality of imaging devices 2205; produce a tree model of the patient'svascular system, wherein the tree model comprises geometric measurementsof the patient's vascular system at one or more locations along a vesselcenterline of at least one branch of the patient's vascular system,using at least some of the plurality of captured 2D images; and producea model of flow characteristics of the tree model.

In some embodiments a synchronization unit (not shown) is used toprovide the imaging devices 2205 with a synchronization signal forsynchronizing the capturing of 2D images of the patient's vascularsystem.

Reference is now made to FIG. 12B, which is a simplified illustration ofanother hardware implementation of a system for vascular assessmentconstructed according to an example embodiment of the invention.

The Example System of FIG. 12B Includes:

One imaging device 2235 for capturing a plurality of 2D images of thepatient's vascular system and a computer 2210 functionally connected2239 to the imaging device 2235.

In the example embodiment of FIG. 12B, the imaging device 2235 isconfigured to obtaining the 2D images from two or more directions withrespect to the subject. The direction and location of the imaging device2235 with respect to the subject, and/or with respect to a fixed frameof reference, are optionally recorded, optionally to aid in producing avessel tree model, whether 1 dimensional (1D) or three dimensional (3D),from 2D Images taken by the imaging device 2235.

The computer 2210 is optionally configured to: accept data from theplurality of imaging device 2235; produce a tree model of the patient'svascular system, wherein the tree model comprises geometric measurementsof the patient's vascular system at one or more locations along a vesselcenterline of at least one branch of the patient's vascular system,using at least some of the plurality of captured 2D images; and producea model of flow characteristics of the tree model.

In some embodiments a synchronization unit (not shown) is used toprovide the imaging device 2235 with a synchronization signal forsynchronizing the capturing of 2D images of the patient's vascularsystem, optionally at a same phase during the cardiac cycle.

In some embodiments the computer 2210 accepts a subject's ECG signal(not shown), and selects 2D images from the imaging device 2235according to the ECG signal, for example in order to select 2D images ata same cardiac phase.

In some embodiments, the system of FIG. 12A or 12B includes an imageregistration unit which detects corresponding image features in the 2Dimages; calculates image correction parameters based on thecorresponding image features; and registers the 2D images so the imagefeatures correspond geometrically.

In some embodiments the image features are optionally selected as anorigin of the tree model; and/or a location of minimal radius in astenosed vessel; and/or a bifurcation of a vessel.

Potential Benefits of Embodiments of the Invention

Example embodiments of the invention can be minimally invasive, that is,they can refrain from guidewire interrogation of the coronary artery,and therefore minimize danger to a patient, compared to an invasive FFRcatheter procedure.

It is noted that an example embodiment of the invention enablesmeasuring a reliable index during catheterization, providing acost-effective way to potentially eliminate a need for processingangiographic data after the catheterization procedure, and/or foradditional equipment during the catheterization procedure, such as aguidewire, and/or for materials involved in a catheterization procedure,such as adenosine. It is noted that another potential saving includes asaving in hospitalization costs following better treatment decisions.

An example embodiment of the invention optionally enables trying outvarious post-inflation vessel cross sections in various post-inflationmodels of the vascular system, and selecting a suitable stent for asubject based on desired flow characteristics of the post-inflationmodel.

An example embodiment of the invention optionally automaticallyidentifies geometrical characteristics of a vessel, defines an outercontour of the vessel, and optionally provides relevant hemodynamicinformation associated with the vessel, corresponding to the present-dayinvasive FFR method.

An embodiment of the invention optionally generates an index indicativeof a need for coronary revascularization. The minimally invasiveembodiment of the invention potentially prevents unnecessary risk topatients, potentially reduces total time and cost of an angiography,hospitalization and follow-up.

A system constructed according to an example embodiment of the inventionpotentially enables shortening the diagnostic angiography procedure.Unnecessary coronary interventions during angiography and/or in thefuture are also potentially prevented. Also, a method according to anexample embodiment of the invention optionally enables assessment ofvascular problems in other arterial territories, such as carotidarteries, renal arteries, and diseased vessels of the limbs.

It is noted that resolution of angiographic images is typically higherthan resolution typically obtained by 3D techniques such a CT. A modelconstructed from the higher resolution angiographic images can beinherently higher resolution, and provide greater geometric accuracy,and/or use of geometric properties of smaller vessels than CT images,and/or calculations using branching vessels distal to a stenosis formore generations, or bifurcations, downstream from the stenosis than CTimages.

a short list of potential non-invasive FFR benefits includes:

a non-invasive method which does not endanger the patient;

a computational method without additional time or invasive equipment;

a prognostic benefit in ‘borderline’ lesions and in multi-vesseldisease;

provides a reliable index to assess the need for coronaryrevascularization;

a method to assess and/or optimize revascularization procedures;

a strategy which saves cost of catheterization, hospitalization andfollow-up;

preventing unnecessary coronary interventions following angiography; and

a ‘one-stop shop’ comprehensive lesion assessment.

Another benefit of the present embodiments is the ability to produce atree model within a short period of time. This allows calculating ofindices, particularly but not necessarily, indices that are indicativeof vascular function (e.g., FFR) also within a short period of time(e.g., within less than 60 minutes or less than 50 minutes or less than40 minutes or less than 30 minutes or less than 20 minutes from the timeat which the 2D images are received by the computer). Preferably, theindex is calculated while the subject is still immobilized on thetreatment surface for the porpoise of catheterization. Such fastcalculation of index is advantageous since it allows the physician toget the assessment for a lesion being diagnosed during thecatheterization procedure, and thus enable quick decision regarding theproper treatment for that lesion. The physician can determine thenecessity of treatment while being in the catheterization room, and doesnot have to wait for an offline analysis.

Additional advantageous of fast calculation of index include, reducedrisk to the patient, ability to calculate the index without the need ofdrugs or invasive equipment, shortening of the duration of coronarydiagnostic procedure, established prognostic benefit in borderlinelesions, reduced costs, reduced number of unnecessary coronaryinterventions and reduced amount of subsequent procedures.

The In this “game” of assessing the hemodynamic severity of each lesion,a non-real-time solution is not a considered option. The physician needsto know whether to treat the lesion in the cath lab or not, and can'tafford to wait for an offline analysis. CT-based solutions are also partof a different “game”, since the utilization of cardiac CT scans is lowcompared to PCI procedures, and the resolution, both temporal andspatial, is much lower compared to angiograms.

Another point to stress, is that the on-line image-based FFR evaluation,unlike the invasive evaluation, will allow to assess any borderlinelesion, and won't be necessarily limited to the percentage of lesionsevaluated nowadays, since the risk to the patient, and the cost will bea lot lower.

It is expected that during the life of a patent maturing from thisapplication many relevant methods and systems for imaging a vascularsystem will be developed and the scope of terms describing imaging areintended to include all such new technologies a priori.

The terms “comprising”, “including”, “having” and their conjugates mean“including but not limited to”.

The term “consisting of” is intended to mean “including and limited to”.

The term “consisting essentially of” means that the composition, methodor structure may include additional ingredients, steps and/or parts, butonly if the additional ingredients, steps and/or parts do not materiallyalter the basic and novel characteristics of the claimed composition,method or structure.

As used herein, the singular form “a”, “an” and “the” include pluralreferences unless the context clearly dictates otherwise. For example,the term “a unit” or “at least one unit” may include a plurality ofunits, including combinations thereof.

The words “example” and “exemplary” are used herein to mean “serving asan example, instance or illustration”. Any embodiment described as an“example or “exemplary” is not necessarily to be construed as preferredor advantageous over other embodiments and/or to exclude theincorporation of features from other embodiments.

The word “optionally” is used herein to mean “is provided in someembodiments and not provided in other embodiments”. Any particularembodiment of the invention may include a plurality of “optional”features unless such features conflict.

As used herein the term “method” refers to manners, means, techniquesand procedures for accomplishing a given task including, but not limitedto, those manners, means, techniques and procedures either known to, orreadily developed from known manners, means, techniques and proceduresby practitioners of the chemical, pharmacological, biological,biochemical and medical arts.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the invention, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable sub-combination or as suitable in any other describedembodiment of the invention. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

Although the invention has been described in conjunction with specificembodiments thereof, it is evident that many alternatives, modificationsand variations will be apparent to those skilled in the art.Accordingly, it is intended to embrace all such alternatives,modifications and variations that fall within the spirit and broad scopeof the appended claims.

All publications, patents and patent applications mentioned in thisspecification are herein incorporated in their entirety by referenceinto the specification, to the same extent as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated herein by reference. Inaddition, citation or identification of any reference in thisapplication shall not be construed as an admission that such referenceis available as prior art to the present invention. To the extent thatsection headings are used, they should not be construed as necessarilylimiting.

What is claimed is:
 1. A method for vascular assessment comprising:receiving a plurality of 2D angiographic images of a portion of avasculature of a subject, and processing said images to produce astenotic model over the vasculature, said stenotic model havingmeasurements of the vasculature at one or more locations along vesselsof the vasculature; obtaining a flow characteristic of the stenoticmodel; and calculating an index indicative of vascular function, based,at least in part, on the flow characteristic in the stenotic model. 2.The method according to claim 1, wherein said measurements of thevasculature are at one or more locations along a centerline of at leastone branch of the vasculature.
 3. The method according to claim 1,wherein said flow characteristic of said stenotic model comprisesresistance to fluid flow.
 4. The method according to claim 3, furthercomprising identifying in said first stenotic model a stenosed vesseland a crown of said stenosed vessel, and calculating said resistance tofluid flow in said crown; wherein said index is calculated based on avolume of said crown, and on a contribution of said stenosed vessel tosaid resistance to fluid flow.
 5. The method according to claim 1,wherein said flow characteristic of said stenotic model comprises fluidflow.
 6. The method according to claim 1, wherein said stenotic model isa three-dimensional vessel tree.
 7. The method according to claim 6,wherein said vessel tree comprises data pertaining to location,orientation and diameter of vessels at a plurality of points within saidportion of the vasculature.
 8. The method according to claim 1, whereinsaid processing said images to produce said stenotic model comprises:extending said stenotic model by one bifurcation; calculating a new flowcharacteristic in said extended stenotic model; updating said indexresponsively to said new flow characteristic and according to apredetermined criterion; and iteratively repeating said extending, saidcalculating and said updating.
 9. The method according to claim 1,further comprising processing said images to produce a second model oversaid vasculature, and obtaining a flow characteristic of said secondmodel; wherein said calculation of said index is based on the flowcharacteristic in the stenotic model and on the flow characteristic inthe second model.
 10. The method according to claim 9, wherein saidsecond model is a normal model, comprising an inflated vessel replacinga stenotic vessel in the stenotic model.
 11. The method according toclaim 9, wherein said stenotic model is a three-dimensional vessel treeand said second model is a second three-dimensional vessel tree.
 12. Themethod according to claim 9, wherein said flow characteristics of saidmodels comprise fluid flow.
 13. The method according to claim 9, whereinsaid flow characteristics of said models comprise resistance to fluidflow.
 14. The method according to claim 9, wherein each of the modelscorresponds to a portion of the vasculature which is between twoconsecutive bifurcations of the vasculature and which includes astenosis.
 15. The method according to claim 9, wherein each of themodels corresponds to a portion of the vasculature which includes abifurcation of the vasculature.
 16. The method according to claim 9,wherein each of the models corresponds to a portion of the vasculaturewhich includes a stenosis and which extends at least one bifurcation ofthe vasculature beyond the stenosis.
 17. The method according to claim9, wherein each of the models corresponds to a portion of thevasculature which includes a stenosis and which extends at least threebifurcations of the vasculature beyond the stenosis.
 18. The methodaccording to claim 16, wherein each of the models corresponds to aportion of the vasculature which includes a stenosis and which extendsdistally as far as resolution of said images allows.
 19. The methodaccording to claim 9, wherein said stenotic model corresponds to aportion of the vasculature which includes a stenosis, and said secondmodel corresponds to a portion of the vasculature which does not includea stenosis and which is geometrically similar to the stenotic model. 20.The method according to claim 9, wherein said processing said images toproduce said stenotic model and said second model comprises: extendingeach of the models by one bifurcation; calculating a new flowcharacteristic in each extended model; updating said index responsivelyto said new flow characteristics and according to a predeterminedcriterion; and iteratively repeating said extending, said calculatingand said updating.
 21. The method according to claim 9, wherein saidindex is calculated based on a ratio of the flow characteristic in thestenotic model to the flow characteristic in the second model.
 22. Themethod according to claim 1, wherein said index is indicative of theneed for revascularization.
 23. The method according to claim 1, furthercomprising obtaining a Fractional Flow Ratio (FFR) based on said index.24. The method according to claim 1, further comprising determining,based on said index, a ratio between maximal blood flow in an area of astenosis and a maximal blood flow in a same area without stenosis. 25.The method according to claim 1, further comprising capturing said 2Dimages.
 26. A computer software product, comprising a computer-readablemedium in which program instructions are stored, which instructions,when read by a computer, cause the computer to receive a plurality of 2Dimages of a subject's vasculature and execute the method according toclaim
 1. 27. A system for vascular assessment comprising: a plurality ofimaging devices configured for capturing a plurality of 2D images of avasculature of a subject; and a computer configured for receiving saidplurality of 2D images and executing the method according to claim 1.